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Memristor‐Based Biologically Plausible Memory Based on Discrete and Continuous Attractor Networks for Neuromorphic Systems

  • Published:2020-02-20 Issue:3 Volume:2 Page:2000001
  • ISSN:2640-4567
  • Container-title:Advanced Intelligent Systems
  • language:en
  • Short-container-title:Advanced Intelligent Systems

Author:

Wang Yanghao1,Yu Liutao2,Wu Si2,Huang Ru134,Yang Yuchao134ORCID

Affiliation:

1. Key Laboratory of Microelectronic Devices and Circuits (MOE)Department of Micro/NanoelectronicsPeking University Beijing 100871 China

2. School of Electronics Engineering and Computer SciencePeking University Beijing 100871 China

3. Academy for Artificial IntelligencePeking University Beijing 100871 China

4. Frontiers Science Center for Nano-optoelectronicsPeking University Beijing 100871 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Reference32 articles.

1. Neuromorphic electronic systems

2. C. D.Schuman T. E.Potok R. M.Patton J. D.Birdwell M. E.Dean G. S.Rose J. S.Plank.2017 arXiv:1705.06963.

3. Shannon-Inspired Statistical Computing for the Nanoscale Era

4. Memristor-The missing circuit element

5. The missing memristor found

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1. Unsupervised Classification of Spike Patterns with the Loihi Neuromorphic Processor;Electronics;2024-08-13

2. Memristor and spintronics as key technologies for upcoming computing resources;Nanoscale Memristor Device and Circuits Design;2024

3. ViM: Vision Middleware for Unified Downstream Transferring;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Dual functional states of working memory realized by memristor-based neural network;Frontiers in Neuroscience;2023-06-07

5. Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06
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